Bibliographic record
Abstract
The purpose of this presentation is to describe the characteristics of a group of multiple role active women and to determine if there were differences according to passion group on physical activity (PA) levels, sleep compromise and physical pain experienced in the previous month. It was hypothesized that obsessively passionate women (OP) would report higher levels of PA, would compromise sleep to a greater extent and would report higher levels of pain then harmoniously passionate women (HP) and non passionate women (NP). Sixty six women were recruited. Participants had to be employed full-time, have a least one child at home and engage in recommended levels of PA. Women were considered passionate about PA if they scored above the midpoint (4) on the 4 items of the passion scale (Vallerand, 2003). Then, those that were passionate were classified into groups (harmonious versus obsessive) corresponding to their highest standardized score on the 2 subscales (Vallerand & Houlfort, 2003). Results revealed that this group of women were middle-aged (mean age: 42.6 years), highly active (mean Godin score of 52.6), passionate about PA (63 of the 66 were passionate with 28 being obsessively passionate) and slightly under slept (mean hours sleep: 6.8 hours). Significant differences were revealed on level of PA and sleep compromise. Specifically, both passion groups reported higher levels of PA then the non passion group (OP: 58.2, HP: 49.7, NP: 33.3) and that the obsessively passionate group compromised sleep more compared to the harmoniously passionate groups and the non passionate group who did not compromise sleep at all. Results are discussed in line with the dualistic model of passion and implications for wellness promotion in women are drawn.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".